Many methods of ortholog inference have been proposed, and their comparative performance has been reviewed.

These methods belong to the two major classes of approaches:

1. identify all homologs in a set of species and then attempt to distinguish between orthologs and paralogs by analyzing the distribution of the genes from different species
across the tips of the tree

2. use a heuristic to compile the pairs of genes, each in a different genome, that are each other’s best-scoring matches,SymBets, for symmetric best hits

Class I:

Evola (http://www.h-invitational.jp/evola/) contains ortholog information of all human genes among vertebrates.

HOGENOM : Database of Complete Genome Homologous Genes Families

http://pbil.univ-lyon1.fr/databases/hogenom/acceuil.php

http://pbil.univ-lyon1.fr/databases/hovergen.php

Class II:

eggNOG (evolutionary genealogy of genes: Non-supervised Orthologous Groups) is a database of orthologous groups of genes. The orthologous groups are annotated with functional description lines (derived by identifying a common denominator for the genes based on their various annotations), with functional categories (i.e derived from the original COG/KOG categories).

http://eggnog.embl.de/

Eukaryotic Gene Orthologues (EGO) at DFGI are generated by pair-wise comparison between the Tentative Consensus (TC) sequences that comprise the Dana Farber Gene Indices from individual organisms. The reciprocal pairs of the best match were clustered into individual groups and multiple sequence alignments were displayed for each group. The EGO database can be accessed through the SEARCH function. The release notes for the current EGO can also be referenced.

http://compbio.dfci.harvard.edu/tgi/ego/

http://www.orthomcl.org/cgi-bin/OrthoMclWeb.cgi

The Hierarchical Catalog of Eukaryotic Orthologs

http://cegg.unige.ch/orthodb3

http://inparanoid.sbc.su.se/cgi-bin/index.cgi

MultiParanoid

http://multiparanoid.sbc.su.se/

http://msoar.cs.ucr.edu/

http://omabrowser.org/cgi-bin/gateway.pl

http://oxytricha.princeton.edu/BlastO/

Other method:

TreeFam (Tree families database) is a database of phylogenetic trees of animal genes. It aims at developing a curated resource that gives reliable information about ortholog and paralog assignments, and evolutionary history of various gene families.

TreeFam defines a gene family as a group of genes that evolved after the speciation of single-metazoan animals. It also tries to include outgroup genes like yeast (S. cerevisiae and S. pombe) and plant (A. thaliana) to reveal these distant members.

TreeFam is also an ortholog database. Unlike other pairwise alignment based ones, TreeFam infers orthologs by means of gene trees. It fits a gene tree into the universal species tree and finds historical duplications, speciations and losses events. TreeFam uses this information to evaluate tree building, guide manual curation, and infer complex ortholog and paralog relations.

The basic elements of TreeFam are gene families that can be divided into two parts: TreeFam-A and TreeFam-B families. TreeFam-B families are automatically created. They might contain errors given complex phylogenies. TreeFam-A families are manually curated from TreeFam-B ones. Family names and node names are assigned at the same time. The ultimate goal of TreeFam is to present a curated resource for all the families.